7 papers
Evidence aggregation with ignorance in mind: learning what we do (not) know for archetypes discovery
Emily Breza, Arun G. Chandrasekhar, Davide Viviano
When evaluating policy interventions, researchers often pursue two related goals: identifying which individuals or contexts benefit most, and determining whether patterns of treatm…
Program Evaluation with Remotely Sensed Outcomes
Ashesh Rambachan, Rahul Singh, Davide Viviano
We study causal inference in experiments and quasi-experiments, where the economic outcome is imperfectly measured by a remotely sensed variable. The remotely sensed variable is lo…
Causal clustering: design of cluster experiments under network interference
Davide Viviano, Lihua Lei, Guido Imbens +3
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. We provide a framework to choose the clustering…
Estimating Social Norm Complementarities
Eliana La Ferrara, Cheaheon Lim, Davide Viviano
We develop a model of choice over social norms that allows for complementarities along two dimensions: \textit{technological}, analogous to complementarities between consumption go…
Triply Robust Panel Estimators
Susan Athey, Guido Imbens, Zhaonan Qu +1
This paper studies estimation of causal effects in a panel data setting. We introduce a new estimator, the Triply RObust Panel (TROP) estimator, that combines (i) a flexible model…
Learning What to Learn: Experimental Design when Combining Experimental with Observational Evidence
Aristotelis Epanomeritakis, Davide Viviano
Experiments deliver credible treatment-effect estimates but, because they are costly, are often restricted to specific sites, small populations, or particular mechanisms. A common…